In this paper, we investigate the dynamic relationship between economic uncertainty in China and share prices in the Chinese airline industry, focusing on periods of market crisis. Using daily data from January 2015 to June 2022 and covering major crisis events, including the China stock market crash, US-China trade war, COVID-19 pandemic, and Russia-Ukraine war coinciding with Shanghai's lockdown, we employed Time-Varying Parameter Vector Autoregression (TVP-VAR) connectedness and Quantile-on-Quantile regression methodologies to examine dynamic spillover effects between Chinese economic policy uncertainty (EPU) and individual airline stocks across market conditions. We found that policy uncertainty transforms from a passive recipient to the dominant spillover transmitter only during the most severe crisis (2022 Russia-Ukraine war/Shanghai lockdown), with total connectedness reaching 82.82% compared to 60% in normal periods, and that state-owned airlines exhibit systematically higher sensitivity to policy uncertainty during stable market conditions, while private airlines show greater resilience. These findings challenge the conventional view that policy uncertainty uniformly affects all firms within a sector, revealing that crisis severity and firm characteristics jointly determine vulnerability patterns, with critical implications for portfolio diversification strategies and policy coordination mechanisms in emerging market economies where government intervention plays a central role in economic stability.
Citation: Ran Wu, Shenglin Ma, Hongjun Zeng. Impact of economic policy uncertainty on Chinese airline stocks: Evidence from recent crisis periods using TVP-VAR connectedness and quantile-on-quantile analysis[J]. Quantitative Finance and Economics, 2026, 10(1): 162-187. doi: 10.3934/QFE.2026008
In this paper, we investigate the dynamic relationship between economic uncertainty in China and share prices in the Chinese airline industry, focusing on periods of market crisis. Using daily data from January 2015 to June 2022 and covering major crisis events, including the China stock market crash, US-China trade war, COVID-19 pandemic, and Russia-Ukraine war coinciding with Shanghai's lockdown, we employed Time-Varying Parameter Vector Autoregression (TVP-VAR) connectedness and Quantile-on-Quantile regression methodologies to examine dynamic spillover effects between Chinese economic policy uncertainty (EPU) and individual airline stocks across market conditions. We found that policy uncertainty transforms from a passive recipient to the dominant spillover transmitter only during the most severe crisis (2022 Russia-Ukraine war/Shanghai lockdown), with total connectedness reaching 82.82% compared to 60% in normal periods, and that state-owned airlines exhibit systematically higher sensitivity to policy uncertainty during stable market conditions, while private airlines show greater resilience. These findings challenge the conventional view that policy uncertainty uniformly affects all firms within a sector, revealing that crisis severity and firm characteristics jointly determine vulnerability patterns, with critical implications for portfolio diversification strategies and policy coordination mechanisms in emerging market economies where government intervention plays a central role in economic stability.
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Figures(4) / Tables(8)
Ran Wu, Shenglin Ma, Hongjun Zeng. Impact of economic policy uncertainty on Chinese airline stocks: Evidence from recent crisis periods using TVP-VAR connectedness and quantile-on-quantile analysis[J]. Quantitative Finance and Economics, 2026, 10(1): 162-187. doi: 10.3934/QFE.2026008
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